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Abschätzung der Gesamtzahl Schwerstverletzter in Folge von Straßenverkehrsunfällen in Deutschland
(2010)
Die Zahlen der im Straßenverkehr Getöteten, Schwer- und Leichtverletzten werden in Deutschland seit Jahren in amtlichen Statistiken geführt. Über die Gruppe der besonders schwer betroffenen Patienten liegen jedoch nur vage Schätzungen vor. Auch werden unterschiedliche Kriterien zur Definition dieser so genannten Schwerstverletzten verwendet, die zumeist auf einer Beschreibung der Art und der Schwere der Verletzungen beruhen. In der vorliegenden Arbeit sollen mit Daten aus dem Trauma-Register der DGU sowohl die unterschiedlichen Definitionen dargestellt werden, als auch über verschiedene Methoden die Gesamtzahl dieser Personen in Deutschland geschätzt werden. Das TraumaRegister DGU (TR-DGU) ist eine freiwillige Dokumentation von Unfallopfern, die lebend eine Klinik erreichen, dort behandelt werden und intensivmedizinisch betreut werden müssen. Das Register besteht seit 1993 und erfasst derzeit etwa 6.000 Fälle pro Jahr aus über 100 Kliniken. Pro Patient werden ca. 100 Angaben einschließlich der Codierung seiner Verletzungen gemäß Abbreviated Injury Scale (AIS) erfasst. Dieser Codierung erlaubt die Berechnung des Injury Severity Score (ISS) und des New ISS (NISS). Zum Vergleich werden folgende Definitionen eines Schwerstverletzten betrachtet: Maximum AIS ≥ 3; Maximum AIS ≥ 4; ISS ≥ 9; ISS ≥ 16; NISS ≥ 16, Polytrauma sowie die Notwendigkeit der Intensivtherapie. Am Beispiel des Kriteriums "ISS ≥ 16" werden schließlich auf drei verschiedene Arten die Gesamtzahl Schwerstverletzter Verkehrsunfallopfer geschätzt: 1.) in fünf ausgewählten Regionen werden die Schwerstverletzten aus dem TR-DGU mit der Anzahl Schwerverletzter aus der amtlichen Statistik verglichen, um den Anteil der besonders schwer betroffenen Patienten zu bestimmen. 2.) Aus dem TR-DGU wird je nach Versorgungsstufe des Krankenhauses (lokales, regionales oder überregionales Zentrum) die durchschnittliche Anzahl Schwerstverletzter ermittelt und dann über die Anzahl solcher Kliniken in Deutschland hochgerechnet. 3.) Die Zahl der Schwerstverletzten wird aus der Zahl der Getöteten Verkehrsunfallopfer geschätzt. Dazu nutzt man das Verhältnis von in der Klinik verstorbenen zu überlebenden Schwerstverletzten aus dem TR-DGU. Mit Literaturangaben zum Anteil von präklinisch Verstorbenen wird dann auf der Basis der Anzahl der Getöteten aus der amtlichen Statistik die Gesamtzahl Schwerstverletzter geschätzt. Je nach Definition eines Schwerstverletzten konnten zwischen 9.213 und 17.425 Fälle aus dem TR-DGU der letzten 10 Jahre berücksichtigt werden. Von diesen Patienten sind zwischen 12,7% und 20,2% im Krankenhaus verstorben. Die Krankenhaus Liegedauer der Überlebenden liegt zwischen 30 und 35 Tagen. Nimmt man die Definition "ISS -³ 16" als Basis (n=13.467), so reduziert sich die Zahl Schwerstverletzter um 37%, wenn man stattdessen den Begriff des Polytraumas wählt; betrachtet man hingegen die Intensivpflichtigkeit als Kriterium so erhöht sich die Zahl um 22%. Der erste Schätzansatz kommt zum Ergebnis, dass etwa 8-10% der Schwerverletzten zu den besonders schwer Verletzten zählen. Für ganz Deutschland erhält man damit Schätzwerte zwischen 6.300 und 7.900 Fälle pro Jahr. Die zweite Methode ergab, dass die Krankenhäuser der drei unterschiedlichen Versorgungsstufen jeweils 30,2, 11,5 oder 3,3 Fälle pro Jahr behandeln. Bezogen auf die 874 deutschen Kliniken ergeben sich geschätzte Gesamtzahlen von 6.800 bis 10.400 Fälle. Die dritte Methode zeigt, dass pro Patient, der im Krankenhaus verstirbt, 6,3 Schwerstverletzte überleben. Im Krankenhaus versterben jedoch etwa nur 25% bis 40% der insgesamt Getöteten; der Großteil der Getöteten verstirbt unmittelbar an der Unfallstelle. Damit müssen noch 1,5 bis 3 Todesfälle hinzugerechnet werden, was schließlich zu einem Verhältnis von 6,3 Schwerstverletzten zu 2,5 bis 4 Todesfällen führt. Bei einer Gesamtzahl von 5.595 Getöteten (Mittelwert 2002-2008) ergeben sich so Gesamtzahlen von 8.800 bis 14.000 Schwerstverletzte pro Jahr. Die Ergebnisse der angewendeten Schätzmethoden variieren stark und lassen auf eine Gesamtzahl von etwa 10.000 schwerstverletzten Verkehrsunfallopfern pro Jahr in Deutschland schließen. Bei Anwendung der Definition Intensivtherapie ergeben sich sogar etwa 12.500 Fälle. Alle Schätzmethoden sind gewissen Unsicherheiten ausgesetzt, die wenn möglich in Variationsrechnungen berücksichtigt wurden. Eine deutlich verbesserte Schätzung dieser Zahl ist jedoch erst möglich, wenn in wenigen Jahren vollzählige Erfassungen aus den derzeit entstehenden regionalen TraumaNetzwerken der DGU im TraumaRegister vorliegen.
Car occupants have a high level of mortality in road accidents, since passenger cars are the prevalent mode of transport. In 2013, car occupant fatalities accounted for 45% of all road accident fatalities in the EU. The objective of this research is the analysis of basic road safety parameters related to car occupants in the European countries over a period of 10 years (2004-2013), through the exploitation of the EU CARE database with disaggregate data on road accidents. Data from the EU Injury Database for the period 2005 - 2008 are used to identify injury patterns, and additional insight into accident causation for car occupants is offered through the use of in-depth accident data from the EC SafetyNet project Accident Causation System (SNACS). The results of the analysis allow for a better understanding of the car occupants' safety situation in Europe, thus providing useful support to decision makers working for the improvement of road safety level in Europe.
The overall purpose of the ASSESS project is to develop a relevant and standardised set of test and assessment methods and associated tools for integrated vehicle safety systems, primarily focussing on currently available pre-crash sensing systems. The first stage of the project was to define casualty relevant accident scenarios so that the test scenarios will be developed based on accident scenarios which currently result in the greatest injury outcome, measured by a combination of casualty severity and casualty frequency. The first analysis stage was completed using data from a range of accident databases, including those which were nationally representative (STATS19, UK and STRADA, SE) and in-depth sources which provided more detailed parameters to characterise the accident scenarios (GIDAS, DE and OTS, UK). A common analysis method was developed in order to compare the data from these different sources, and while the data sets were not completely compatible, the majority of the data was aligned in such a way that allowed a useful comparison to be made. As the ASSESS project focuses on pre-crash sensing systems fitted to passenger cars, the data selected for the analysis was "injury accidents which involved at least one passenger car". The accident data analysis yielded the following ranked list of most relevant accident scenarios: Rank Accident scenario 1 Driving accident - single vehicle loss of control 2 Accidents in longitudinal traffic (same and opposite directions) 3 Accidents with turning vehicle(s) or crossing paths in junctions 4 Accidents involving pedestrians The ranked list highlights the relatively large role played by "accidents in longitudinal traffic", and "accidents with turning vehicle(s) or crossing paths in junctions" (the second and third most prevalent accident scenarios, respectively). The pre-crash systems addressed in ASSESS propose to yield beneficial safety outcomes with specific regard to these accident scenarios. This indicates that the ASSESS project is highly relevant to the current casualty crash problem. In the second stage of the analysis a selection of these accident scenarios were analysed further to define the accident parameters at a more detailed level .This paper describes the analysis approach and results from the first analysis stage.
This paper uses the national accident statistics of Great Britain to evaluate the effectiveness of Electronic Stability Control Systems (ESC) to reduce crash involvement rates. The crash experience of 8,951 cars is analysed and compared to a closely matching set of non-ESC cars using case-control methods. This is one of the largest ESC samples analysed to date. Overall the cars with ESC are involved in 3% fewer crashes although the effectiveness is substantially higher under conditions of adverse road friction. ESC equipped cars are involved in 15% fewer fatal crashes although this reduction represents the combined effect of ESC and passive safety improvements.
Crash involvement studies using routine accident and exposure data : a case for case-control designs
(2009)
Fortunately, accident involvement is a rare event: the chance of an individual road user trip to end up in a crash is close to zero. Thus, according to general epidemiological principles one can expect the case-control study design to be especially suitable for quantifying the relative risk (odds ratio) of accident involvement of road users with a certain risk factor as compared to road users that do not have this characteristic. Ideally, of course, the database for such a case-control study should be established by drawing two independent random samples of cases (accidental units) and controls (nonaccidental units), respectively. If, however, special data collection is not an option, it is nevertheless possible to analyze routine accident and exposure data under a case-control design in order to fully exploit the information contained in already existing databases. As a prerequisite, accident and exposure data from different sources are to be combined in a single file of micro or grouped data in a way consistent with the case-control study design. Among other things, the proposed methodological approach offers the possibility to use in-depth data of the GIDAS type also in investigations of active vehicle safety by combining this data with appropriate vehicle trip data collected in mobility surveys.
Es erfolgt eine Aktualisierung und Neufassung des von der Bundesanstalt für Straßenwesen (BASt) im Jahre 1978 veröffentlichten Berichts "Nachtunfälle - eine Analyse auf der Grundlage der Daten der amtlichen Straßenverkehrsunfallstatistik" (Brühning, Hippchen und Weißbrodt; 1978). Ausgewertet werden die Unfalldaten seit 1970, im Wesentlichen aber die Daten des Jahres 1985. Nachtunfälle haben innerhalb des gesamten Unfallgeschehens eine besondere Bedeutung. Sie sind im Mittel schwerer als Unfälle bei Tage: über 25 % aller Unfälle mit Personenschaden, aber rund 40 % aller Unfälle mit Getöteten ereignen sich nachts. Fußgänger werden zu 48,7 % bei Nachtunfällen getötet, 43,1 % der getöteten Pkw-Insassen sterben bei Nachtunfällen. Das Unfallrisiko ist nachts erheblich größer als bei Tage. Nachts steigt das fahrleistungsbezogene Unfallrisiko der Pkw außerorts (ohne BAB) auf das 1,7-fache, auf BAB auf das 1,5-fache des Risikos bei Tage an. Neben Angaben zur zeitlichen Entwicklung erfolgt zunächst ein Überlick über die wesentlichen Kenngrößen (Art der Verkehrsbeteiligung, Alter und Geschlecht der Fußgänger beziehungsweise Fahrer, Ortslage, Unfallmonat, Wochentag und Uhrzeit, Straßenzustand, Unfalltyp und Unfallursachen) des nächtlichen Unfallgeschehens. Darüberhinaus wird eine eingehende Betrachtung zu ausgewählten Problembereichen auf der Grundlage von Tabellenanalysen sowie multidimensionalen Analysen mittels Logit-Modellen durchgeführt. Im einzelnen handelt es sich um die Problembereiche "Alkohol", ungünstiger Straßenzustand, junge Fahrer von motorisierten Zweirädern, Pkw-Fahrer und Fußgänger. Desweiteren wird auf regionale Unterschiede nach Bundesländern im nächtlichen Unfallgeschehen eingegangen.
Enhanced protection of pedestrians and cyclists remains on the focus. Besides infrastructural and behavioral aspects it is necessary to exploit technical solutions placed on motorized vehicles. Accident research needs reliable data as well as national road accident statistics. Changing the view on seriously injured road users is one of the challenges which will substantially contribute to the optimization on future traffic safety. The missing accuracy in the definition of personal injury has a detrimental effect on making cost efficient road safety policy which is not only focused on fatal accidents. The European commission requested that, starting in 2015, all EU member states provide more detailed data on the injury status of road casualties, with special regard to the group of seriously injured. Conventional accident data will always be essential. But to obtain detailed data about driver behavior in real traffic situations further data sources are required. These could be EDR data, data from electronic control units, data from traffic surveys and traffic counting, naturalistic diving studies and field operational tests. Gaining insight into normal as well as critical driver behavior will enable accident researchers to deduct functions estimating the increase or decrease of accident risk associated with certain behaviors or vehicle functions. Also with view to the introduction of highly automated driving functions in the future such data is urgently needed. Computer simulation based tools to estimate the benefits of active safety systems are another step on the way towards the safety assessment of automated driving. It is now the duty of the scientific community to ask the right questions, to develop a methodology and to merge all these data sources into a common framework for the assessment of future traffic safety innovations.
Sowohl die Zahl der im Straßenverkehr Getöteten wie auch die der Schwerverletzten sind nach Angaben der amtlichen Statistiken in Deutschland seit Jahren rückläufig. Die Gruppe der Schwerverletzten ist allerdings sehr heterogen und umfasst alle Unfallopfer, die für mindestens 24 Stunden in einem Krankenhaus behandelt wurden. Die vorliegende Untersuchung versucht, mit Hilfe von Daten des Traumaregisters der Deutschen Gesellschaft für Unfallchirurgie (DGU) die Frage zu beantworten, ob auch bei den besonders schwer verletzten Verkehrsunfallopfern ein Rückgang der Zahlen zu beobachten ist. Dazu wurden "schwerstverletzte" Patienten definiert als solche, die im Injury Severity Score (ISS) mindestens 9 Punkte erreicht haben und zudem intensivmedizinisch behandelt werden mussten. Der Zeitraum der Untersuchung umfasst zehn Jahre von 1997 bis 2006, der für einige Fragestellungen zusätzlich in zwei je 5-jährige Phasen unterteilt wurde. Ab 2002 (Phase 2) ist auch eine separate Auswertung für Fahrrad- und Motorradfahrer möglich. Die erste Fragestellung richtete sich auf die Veränderung der Anzahl schwerstverletzter Verkehrsunfallopfer über die Zeit. Dafür wurden die Daten von über 11.000 Patienten aus 67 verschiedenen Kliniken betrachtet. Pro Klinik wurde ein Durchschnittswert für die Anzahl von Verkehrsunfallopfern bestimmt, der dann mit der tatsächlich beobachteten Zahl verglichen wurde. Im Ergebnis zeigte sich, dass die relativen Abweichungen vom Durchschnitt insgesamt nur etwa -±10% betragen und dass kein deutlicher Trend einer Abnahme oder Zunahme der Schwerstverletztenzahlen in den vergangenen 10 Jahren erkennbar ist. In der zweiten Fragestellung wurde untersucht, ob und wie stark ein Rückgang der Letalität zu einem Anstieg der Schwerstverletztenzahlen geführt haben könnte. Es konnte gezeigt werden, dass in den letzten beiden Jahren deutlich weniger Patienten im Krankenhaus verstorben sind, als dies nach ihrer Prognose zu erwarten gewesen wäre. Dieser Rückgang der Letalitätsrate von absolut bis zu 5 (in 2006: Prognose 18% versus beobachtet 13%) trägt damit auch zu einer Zunahme bei der Zahl der Schwerstverletzten bei. Zur Abschätzung der Prognose wurde ein im Traumaregister entwickeltes und validiertes Scoresystem (RISC) eingesetzt. In der letzten Fragestellung sollte geklärt werden, ob sich das Verletzungsmuster bei den Schwerstverletzten in den vergangenen zehn Jahren und abhängig von der Art der Verkehrsteilnahme verändert hat. Insgesamt konnte gezeigt werden, dass der relative Anteil der Autofahrer rückläufig war, von 60% auf 50%. Bei den verletzten Körperregionen zeigt das Schädel-Hirn-Trauma den deutlichsten Rückgang von 69 % auf 60% insgesamt. Dieser Trend ist bei allen Verkehrsbeteiligten erkennbar. Lediglich Verletzungen der Wirbelsäule werden häufiger gesehen, was aber auch ein Effekt der verbesserten CT-Diagnostik sein kann, zum Beispiel beim Ganzkörper-CT. Je nach Art der Verkehrsbeteiligung zeigen sich sehr unterschiedliche Verletzungsmuster. Verletzungen des Kopfes sind bei Radfahrern und Fußgängern dominierend (über 70%), während Motorradfahrer hier die günstigsten Raten zeigen (45%). Motorrad- und Autofahrer haben die höchsten Raten für Verletzungen des Brustkorbs und im Bauchraum, bedingt durch die im Mittel höheren einwirkenden Kräfte auf den Körper. Insgesamt lassen sich die Daten des DGU-Traumaregisters gut nutzen, um typische Verletzungsmuster zu beschreiben und um relative Veränderungen bei der Zahl der Schwerstverletzten über die Zeit nachzuweisen. Beobachtungszeiträume von zehn Jahren und mehr, wie im vorliegenden Fall, ermöglichen auch aktuelle Trendaussagen. Epidemiologische Aussagen wie in den amtlichen Statistiken sind aber nur sehr eingeschränkt möglich, da das Traumaregister bisher nur auf freiwilliger Basis Daten sammelt.
Estimation of the benefits for the UK for potential options to modify UNECE Regulation No. 95
(2010)
The side impact problem in Europe remains substantial. UK data shows that between 22% and 26% of car occupant casualties are involved in a side impact, but this rises to between 29% and 38% for those who are fatally injured. This indicates the more injurious nature of side impacts compared with frontal impacts. The European Enhanced Vehicle safety Committee (EEVC) has performed work to address the side impact issue since 1979. As part of its continuing work, it has recently investigated potential options for regulatory changes to improve side impact protection in cars further. To support this work the UK undertook an analysis to estimate the benefit for potential options to modify UNECE Regulation 95. The analysis used the UK national STATS19 and detailed Co-operative Crash Injury Study (CCIS) accident databases. Of the potential options reviewed, it was found that the addition of a pole test offered the greatest benefit.
The primary goal of this investigation was to determine the relative risk of traffic accidents in students. In a two year period, a survey amongst 2,325 students was carried out, and 3,645 injuries sustained by students treated at our hospital were analyzed. Moped-riding in adolescents were associated with a 23.75-fold increased risk for injury as compared to biking. Children who ride bicycles have a 2.2-fold increased risk for an injury sustained by traffic accidents compared to pedestrians. None of 50 injured bicycle riders with helmet had an AIS for head injuries of more than 2. 24 of 233 injured bicycle drivers without helmet had an AIS for head injuries of more than 2. The use of a protective helmet significantly reduced the severity of head injuries. The level of awareness towards danger and a history of previous accidents correlate with the likelihood of future accidents. Due to the severity of traffic accidents, more adequate prevention measures (wearing of bicycle helmets and better education for moped riders) are urgently needed.
The paper gives an overview of the recent (mostly 2012) figures of killed bus/coach occupants (drivers and passengers) in 27 Member States of the European Union as reported by CARE. The Evolution of the figures of bus/coach occupants killed in road accidents urban, rural without motorway and on motorways from 1991 to 2010 in 15 Member States of the EU supplements this information. More detailed are the figures reported for Germany by the Federal Statistics. The paper displays long-term evaluations (1957 to 2012) for killed, seriously and slightly injured occupants in all kinds of buses/coaches. Midterm evaluations (1995 to 2012) of the figures of fatalities and casualties are displayed for different busses according to their identification of road using as coaches, urban buses, school buses, trolley buses and "other buses". To be able to compare the evolutions of the safety of vehicle occupants it is customary to use different risk indicators. Calculations and illustrations for three often used indicators with their development over time are given: fatalities, seriously injured and slightly injured per 100,000 vehicles registered, per 1 billion (109) vehicle-kilometres travelled and per 1 billion (109) person-kilometres. These indicators are shown for occupants of cars, goods vehicles and buses/coaches. For the period from 1957 until 2012 it is obvious, that for all three vehicle categories analysed there was a clear long-term trend towards more occupant safety in terms of casualties per vehicles registered and per vehicle mileage. This was most significant for car occupants but it can be seen for bus/coach occupants and goodsvehicle occupants as well. Figures of killed occupants and of casualties related to person-kilometres are calculated and displayed for the shorter period 1995 to 2012. Here it becomes obvious that the bus/coach is still the safest mode of transport for the occupants of road vehicles. Graphs for the casualty risk indices still show significantly higher risks for car occupants despite the corresponding curve moved sustainable downwards. It is remarkable, that the risks of being killed or injured for the occupants of urban buses is growing whereas the corresponding risk for the occupants of coaches in line traffic tends downwards. The article ends with a short comparison and discussion of the risk indicators which are actually published for the occupants (driver and passengers) of cars and the passengers of buses/coaches, railroads, trams and airplanes. The interpretation of such information depends on the perception and it seems that for a complete view not only one indicator should be used and the evolutions of the indicator values during longer periods (as displayed with examples in the paper) should also be taken into account.
In the context of this study, different data sources for accident research were examined regarding their possible data access and evaluated concerning the individual quality and extent of the data. Analyses of accidents require detailed and comprehensive information in particular concerning vehicle damages, injury patterns and descriptions of the accident sequence. The police documentation supplies the basic accident statistics and is amended in the context of the forensic treatment by further information, e.g. by medical and technical appraisals and witness questionings. As a new approach to the data acquisition for the analysis of fatal traffic accidents, the information was made usable which was collected by the police and by the investigations of the public prosecutor. The best strategy for obtaining reliable, extensive and complete data consists of combining the information from these two sources: the very complete, but elementary statistic data of the Niedersächsisches Landesamt für Statistik (Lower Saxony State Authority of Statistics), based on the police documentation as well as the very extensive accident information resulting from the investigation documentation of the public prosecutor after conclusion of the procedure, the so-called Court Records. Of all 715 fatal traffic accidents, which happened in the year 2003 in the German State of Lower Saxony, 238 cases were selected by means of a statistically coincidental selective procedure based on a statistically representative manner (every third accident). These cases cover the investigation documents of the 11 responsible public prosecutor- offices, which were requested and evaluated while preserving the data security. Of the 238 cases 202 cases were available, which were individually coded and stored in a data base using 160 variables. Thus a data base of a sample of representative data for fatal accidents in Lower Saxony was set up. The data base contains extensive information concerning general accident data (35 variables), concerning road and road surface data (30 variables), concerning vehicle-specific data (68 variables) as well as concerning personal and injury data (27 variables).
The NHTSA-sponsored Crash Injury Research and Engineering Network (CIREN) has collected and analyzed crash, vehicle damage, and detailed injury data from over 4000 case occupants who were patients admitted to Level-I trauma centers following involvement in motor vehicle crashes. Since 2005, CIREN has used a methodology known as "BioTab" to analyze and document the causes of injuries resulting from passenger vehicle crashes. BioTab was developed to provide a complete evidenced-based method to describe and document injury causation from in-depth crash investigations with confidence levels assigned to the causes of injury based on the available evidence. This paper describes how the BioTab method is being used in CIREN to leverage the data collected from in-depth crash investigations, and particularly the detailed injury data available in CIREN, to develop evidence-based assessments of injury causation. CIREN case examples are provided to demonstrate the ability of the BioTab method to improve real-world crash/injury data assessment.
Nowadays, traffic accidents are recorded in historical databases. Regarding the huge quantity of data, the use of data mining tools is essential to help Experts, for automatically extracting relevant information in order to establish and quantify relations between severity and potential factors of accidents. An innovative approach is here proposed for an in depth investigation of real world accidents data base. Mutual information ratio based on conditional entropies is used to quantity the association strength between an accident outcome descriptor (injury severity) and other potential association factors. Information theoretic methods help to select automatically groups of factors mostly responsible of the severity of accident.
Novice drivers are at high risk for crash involvement. We performed an analysis of causations, injury patterns and distributions of novice drivers in cars and on motorcycles in road traffic as a basis for proper measurements. Method Data of accident and hospital records of novice drivers (licence < 2 years) were analysed focusing the following parameters: injury type, localisation and mechanism, Abbreviated Injury Scale (AIS), maximum AIS (MAIS), delta-v, collision speed and other technical parameters and have been compared to those of experienced drivers. In 18352 accidents in the area of Hannover (years1985"2004), 2602 novice drivers and 18214 experienced drivers were recorded having an accident. Novice car drivers were more often and severe injured than experienced and on motorcycles the experienced riders were at higher risk. Novice drivers of both groups sustained more often extremity injuries. 4.5 % novice car drivers were not restraint compared to 3.7 % of the experienced drivers and 6.1 % novice motorcycle drivers did not wear a proper helmet (versus 6.5 %). Severe injuries sustained at a rate of 20 % at collision speeds below 30 km/h and in 80% at collision speeds above 50 km/h. Novice car drivers drove significant older cars. The risk profile of novice drivers is similar to those of drivers older than 65 years. Structural protection and special lectures like skidding courses could be proper remedial action next to harder punishment of violations.
A lot of factors are related to a road traffic accident; particularly human factors such as road use characteristic, driving maneuver characteristic and safety attitude are the major ones. As a random factor is also included, so it is necessary to minimize the contribution of a random factor to identify human factors related to a road traffic accident. There are several standpoints for traffic accident analysis, such as vehicle-based, location-based and driver-based. And it is effective to analyze driver-based traffic accident data for discussion on the relation between human factors and accidents. An integrated traffic accident database system was developed for analysis considering driver- accident and violation records by ITARD, and several studies were carried out for the evaluation. Useful data for discussion on the relation between types of collision and traffic violations, and the effect of accident experience to the following accident were obtained.
Internationally, the need is expressed for harmonized traffic accident data collection (PSN, PENDANT, etc.). Together with this effort of harmonization, traffic accident investigation moves more and more in the direction of accident causation. As current methods only partly address these needs, a new method was set up. The main characteristics of this method are: • Accident/injury causation (associated) factors can objectively be identified and quantified, by comparison with exposure information from a normal population. • All relevant accident and exposure data can be included: human-, vehicle-, and environmental related data for the pre-crash, crash and postcrash situation (the so-called Haddon matrix). The level of detail can be chosen depending on interest and/or budget, which makes the method very flexible. In this paper the accident collection and control group method are presented, including some of the achieved results from a pilot study on 30 truck accidents and 30 control locations. The data were analyzed by using cross-tabulations and classification-tree analysis. The method proved useful for the identification of statistically significant causational aspects.
This study that was funded by the Research Association for Automotive Technology (FAT) develops a method for the evaluation of the placement of tanks or batteries by using the deformation frequencies in real-world accidents. Therefore, the deformations of more than 20.000 passenger cars in the GIDAS database are analysed. For each vehicle a contour of deformation is calculated and the deformed areas of the vehicles are transferred in a rangy matrix of deformation. Thereby, the vehicle is divided into more than 190.000 cells. Afterwards, all single matrices of deformation are summarized for each cell which allows representative analyses of the deformation frequencies of accidents with passenger cars in Germany. On the basis of these deformation frequencies it is possible to determine least deformed areas of all passenger cars. Furthermore, intended placements of tanks or batteries can be estimated in an early stage of development. Therefore, all vehicles with deformations in the intended tank areas can be analysed individually. Considering numerous parameters out of the GIDAS database (e.g. collision speed, kind of accident, overlap, collision partner etc.) the occurring forces can be calculated or the deformation frequency can be estimated. Furthermore, it is possible to consider the influence of primary and secondary safety systems on the deformation behaviour. The analysis of "worst case accident events" is an additional application of the calculated matrix of deformation frequency.
While the number of fatal accidents is diminishing every year, there is still a need of improvement and action to prevent these deaths. Basis for this purpose has to be an analysis about the factors influencing the car crash mortality. There are various studies describing the univariate influence of several factors, but crash scenarios are too complex to be described by a single variable. The multivariate analysis respects the interference of the variables and gets so to more detailed and representative results. This multivariate analysis is based on about 2,600 cases (the data have been collected by the accident research units Hannover and Dresden (during the years 1999-2003). This paper presents a multivariate model (containing ten different variables) which detects 93% of these cases properly. This means it detects the cases as truly survived and truly death.
Empirical vehicle crashworthiness studies are usually based on national or in-depth traffic accident surveys: Data on accident-involved cars/drivers are analysed in order to quantify the chance of driver injury and to assess certain risk factors like car make and model. As the cars/drivers involved in the same accident form a "cluster", where the size of the cluster equals the number of accident-involved parties, traffic accident survey data are typical multi-level data with accidents as first-level or primary and cars/drivers as secondlevel or secondary units (car occupants in general are to be considered as third level units). Consequently, appropriate statistical multi-level models are to be used for driver injury risk estimation purposes as these models properly account for the cluster structure of traffic accident survey data. In recent years various types of regression models for clustered data have been developed in the statistical sciences. This paper presents multi-level statistical models, which are generally applicable for vehicle crashworthiness assessment in the sense that data on single and multiple car crashes can be analysed simultaneously. As a special case of multi-level modelling driver injury risk estimation based on paired-by-collision car/driver data is considered. It is demonstrated that assessment results may be seriously biased, if the cluster structure inherent in traffic accident survey data is erroneously ignored in the data analysis stage.